The present invention relates to radar doppler processors in general, and more particularly to a pulse doppler radar signal processor which includes an adaptive filter having a delay lattice configuration for enhancing the discrimination of targets from clutter and noise in the radar processing of the received radar signalling.
Modern radars, like the one depicted in the block diagram schematic of FIG. 1, for example, include a variety of means for discriminating targets from clutter and noise. In operation, a transmitter 10 may generate transmission RF energy pulses at either a fixed interpulse period (IPP) as depicted by the time waveform 2A or variable interpulse periods (VIP) as depicted by the time waveform 2B in which exemplary ratios of the varying interpulse periods thereof are designated by the figures: 29':32':31':41':34': . . . under the interpulse periods thereof. The generated RF energy pulses are transmitted into space via a conventional circulator 14 and antenna system 16.
Echo signalling from targets, clutter, chaff, rain, and the like, may be received during the interpulse periods by the antenna system 16 and conducted to a receiver unit 18 via the circulator 14. The received echo signalling may be conditioned from RF to IF or video signalling 20 in the receiver 18 and then sampled and digitized in accordance with predetermined range cells in a conventional sampling analog-to-digital (A/D) converter 22. The range sampled echo signalling may be conducted to post processing apparatus 24 for the detection of targets.
In the example as shown, apparatus 24 includes a moving target indicator (MTI) 26 which may include high pass filters consisting of one or more transfer function parameters to filter out the clutter from the digitized echo signalling based on the spectral characteristics thereof. The transfer function parameters are normally fixed at the design time of the MTI for the optimum removal of a specific type of clutter spectrum or a specific group of clutter types, like rain, chaff, or the like. Generally, the only adaptivity provided in a moving target detection apparatus is that which may be provided in a conventional constant false alarm rate (CFAR) detection unit 28 cascadedly coupled thereto. Normally, the detection threshold level of the CFAR 28 is rendered above the noise plus residue clutter level of the digitized echo signalling. Accordingly, a signal output from the CFAR unit 28 is an indication of a detected moving target.
One of the drawbacks of these type MTI radar processing systems is that if the actual clutter spectrum received by the radar differs from that originally designed for in the response characteristics of the MTI filter 26, then the process for detecting moving targets will be degraded. This phenomenon is illustrated in the graph of FIG. 3 wherein the curve 30 exhibits an exemplary MTI filter response over a doppler frequency spectrum. The response 30 has a primary clutter notch in the region 32 for attenuating clutter in the echo signalling having doppler frequencies within the region 32. One type of target detection degradation may result from a clutter spectrum, such as that shown by the curve 38, for example, being excessive and overlapping the passband of the MTI filter response characteristics 30 wherein that portion of the clutter spectrum as denoted by the shaded area 40 will not be removed and passed accordingly to the CFAR unit 28.
Another drawback may result from attempting to widen the primary clutter notch to include a greater doppler spectrum of clutter in which case secondary clutter notches like the ones shown at 34 and 36 may develop. Accordingly, another type of target detection degradation will result from excessive attenuation of desired echo signalling due to the secondary clutter notches at 34 and 36, for example, which are too wide for practical use. Under these filter response conditions, the echo signalling having doppler frequencies falling within the doppler regions, i.e., 34 and 36, will not pass to the CFAR unit 28 and not be processed for target detection thereby. Of course, it is understood that a combination of these two effects is also very possible.
Another type of moving target detector, one having doppler filter banks, has been applied to the problem of clutter rejection and has been found to provide a slight increase in doppler frequency filter adaptivity by allowing use of independent CFAR detectors on each filter output. Thus, an individual filter response can be varied somewhat to match the clutter characteristics thereof. However, since the actual filter response characteristics must be shaped in advance, the individual filter will be optimum for only that clutter model chosen at the time of design and not for the clutter spectrum actually received by the radar. Such parameters as the main lobe width and position (32) and consequently, the sidelobe levels (34 and 36) as well are normally fixed at the time of the individual filter design.
A further drawback of most of the filter bank type moving target detection systems is that they are suitable for use only with a radar which transmits fixed interpulse periods. Thus, the clutter rejection regions formed by the filter banks are replicated at multiples of the pulse repitition frequency of the radar, more commonly known as blind speed intervals. To insure that target detection is observable over the doppler frequency spectrum, radars generally transmit several observation bursts of pulses, each with a different pulse repetition frequency or carrier frequency for each search resolution range cell in order to observe targets through the blind speeds of the doppler frequency spectrum. Since it is well known that these bursts of pulses must be combined noncoherently, the additional observation time implied by the multiple bursts do not translate into improved spectral or cross range resolution.
There is a certain class of processing filters known as adaptive lattice predictive filters which have been proposed for digital signal processing, in general, and more especially with regard to applications to spectral line enhancement, spectral estimation and speech enhancement signal processing. Examples of these adaptive lattice predictor filters are described in the following references:
(1) N. Ahmed and R. J. Fogler "On An Adaptive Lattice Predictor and a Related Application", IEEE Circuits and Systems Magazine, Vol. 1, No. 4, pgs. 17-23; PA1 (2) J. Makhoul, "Stable and Efficient Lattice Methods for Linear Production", IEEE Transactions on Acoustics, Speech, and Signal Processing, Vol. ASSP-25, No. 5, October, 1977; and PA1 (3) M. Morf, et al, "Efficient Solution of Covariance Equations for Linear Prediction", IEEE Transactions on Acoustics, Speech, and Signal Processing, Vol. ASSP-25, pgs. 429-433, October, 1977.
The tapped weighted delay line or transversal filter type described in the aforementioned papers is operative to linearly predict the contents of a particular range cell from a weighted sum of past data on that range cell and from knowledge of the covariance matrix that represents nearby range cells. In this case, the covariance matrix represents the background to be removed. That part of the incoming data that can be predicted is assumed to be background and is removed by subtraction to form the residue. The residue, then, is composed of the "unpredictable" data: white noise and targets; the filterable clutter has been removed. This type of predictive filter removes clutter by adapting to its spectrum and filtering it out. While being an improvement over the type of clutter filters heretofore described, it also has a drawback of high computational overhead. More specifically, a full N by N covariance matrix must be estimated from the incoming echo signalling and thereafter inverted in the digital signal processing operation. As a result, very high precision arithmetic and apparatus for carrying it out must be used in this type of predictor filter to avoid general round-off problems.
Another of the adaptive lattice predictive filters described in the aforementioned papers provide similar linear prediction processing without the drawback of high precision arithmetic. This other lattice filter is referred to as the delay lattice filter and includes a number of cascaded lattice stages as opposed to a tapped delay line. The delay lattice filter arrangement requires only a scaler correlation estimate to be made for each stage which replaces the N by N covariance matrix inversion step of the tapped delay line, thus alleviating that computational overhead.
Applications of these adaptive lattice predictive filters are primarily proposed for the digital signal processing of data streams coming from speech or seismic measurements which are mostly one dimensional in nature. Since the data streams from speech sources and the like are strictly of a linear form, there is nothing to integrate over except time spent in going from one stage to another stage in the lattice filter. In processing the linear data, there is nothing which really distinguishes delay data from current data, which causes problems in picking the time delays of the various stages and trying to cancel delay data from non-delay data.
In addition, these lattice type filters are proposed to operate only on signals which are stationary or nearly stationary, i.e., their statistics are changing very slowly, because the estimated values of their reflection coefficients k1, k2, . . . can follow only slow variation in input signal statistics as a result of the derivation thereof. This type of processing is adequate if the phase progression of the input signal from stage to stage of the filter will remain fairly constant over a long period of time or vary slowly. On the other hand, in a radar application especially with variable interpule period transmissions, there may be an echo signal phasor that is rotating very rapidly, may be several hundred 2.pi. rotations per second, for example. Accordingly, with variable interpulse period radar operation, the range sampling rate changes so that there is a very rapid variation in phase between the same range samples from range sweep to range sweep, i.e., azimuthal change of the phase progression of a particular input echo signal phasor. The operational capability of the delay lattice linear predictors will not function adequately under this kind of a scenario where the amplitude or phase progression changes by large amounts from sample-to-sample.
To summarize, then, it is of paramount importance to provide a target detection filter in the post processing radar stages that can adapt to the varying clutter and noise spectrums received and generated by the radar to enhance target detection. The class of adaptive lattice predictive filters do offer filter adaptivity for certain types of digital signalling. However, the tapped weighted delay line or transversal filter involves complex matrix manipulations which creates high computational overhead. On the other hand, the delay lattice filter structure can perform the filtering process much simpler but has not as yet been shown to be adequately operational for target detection processing of a radar, especially with regard to variable interpulse period transmissions.